We conducted a retrospective review of DBS surgical patients between 1/2022 and 2/2025, collecting patient demographics, clinical background, DBS hardware information, and neuroimaging. We measured pneumocephalus from intraoperative CT immediately after DBS lead placement using a semi-automated segmentation technique via 3D Slicer. We applied voxel-based morphometry to the preoperative MRI brain using Freesurfer to generate an anatomical list of features for AI analyses, and trained binary classification models to predict the risk of developing significant pneumocephalus during DBS surgery. Our model used a standardized 80-20 training-testing split and model performance was evaluated using a 5-fold cross-validation. Our primary performance metric was the area under the receiver operating curve (AUROC). Secondary metrics were the F1 score, precision, recall and balanced accuracy. 145 patients were included. We defined significant pneumocephalus as any volume greater than 3.000 cm³.